Processor-Tracing Guided Region Formation in Dynamic Binary Translation

NAND flash is preferred for code and data storage in embedded devices due to its high density and low cost. However, NAND flash requires code to be copied to main memory for execution. In inexpensive devices without hardware memory management, full shadowing of an application binary is commonly used to load the program. This approach can lead to a high initial application start-up latency and poor amortization of copy overhead. To overcome these problems, we describe a software-only demand-paging approach that incrementally copies code to memory with a dynamic binary translator (DBT). This approach does not require hardware or operating system support. With careful management, a savings can be achieved in total code footprint, which can offset the size of data structures used by DBT. For applications that cannot amortize full shadowing cost, our approach can reduce start-up latency by 50% or more, and improve performance by 11% on average.

Packet classification is a essential process in network processors. In this process, the incoming packets are matched against a set of filters and divided into specified streams. Classification methods are either software-based or hardware-based. Despite hardware-based methods, software-based methods are more flexible and have a lower cost. This paper reports on an experiment in which the Hierarchical-trie (H-trie) algorithm, which is a software-based method, was for the first time parallelized using the CPU cluster. The characteristic of this algorithm is building a decision tree with the least memory usage and search complexity. We implemented and executed different scenarios by using MPI and OpenMP and combining them in a system with a single multi-core processor as well as multi-core processor clusters. Our results suggest that an increase in the number of processor cores would linearly increase the speed of classification. Moreover, MPI uses more memory than OpenMP but provides a higher rate of classification. The results of the combined method show that, if the number of processes and threads are equal to the number of processor cores, the maximum speed of packet classification can be achieved. Also, the least classification time and memory usage can be achieved when the sum of processes and threads do not outnumber CPU cores.

Dopant-free dicyanofluoranthene-based hole transporting material with low cost enables efficient flexible perovskite solar cells

Recently publish/subscribe (pub/sub) has been a popular paradigm in Internet-scale applications to decouple information publishers and subscribers. The main task of pub/sub is to find those subscriptions that match a given publication. Typically a matching algorithm utilizes a subscription indexing structure for higher efficiency. Unfortunately, given the diverse interests of publishers and subscribers, the semantic space of pub/sub becomes high dimensional and very sparse, leading to nontrivial space cost and inefficient matching algorithm. Existing work paretically tackled the both issues but at cost of scarifying another one, and few can meet the both goals. To overcome this issue, in this paper, we propose a novel coding approach. The approach can not only reduce the space cost of subscription index, and meanwhile helps optimizing the matching efficiency. Our experiments successfully demonstrate the proposed algorithm can achieve not only the low space cost of our proposed subscription indexing but also low running time of matching algorithm.

The natural occurrence, toxicity mechanisms and management strategies of Fumonisin B1：A review

Solar power systems must be competitive with conventional energy sources in in terms of cost to make up a significant portion of the electric power grid. Solar power can likely more rapidly grow and make-up a larger portion of the US power grid if systems have energy storage capability that could continue to provide power for extended periods without sunlight and vary the power as needed (i.e. – be dispatchable). Concentrated solar power tower systems with thermal energy storage using advanced high operating temperature heat transfer fluids and advanced thermodynamic cycles can potentially meet the twin goals of low cost and high reliability while being dispatchable. Molten salts are a promising candidate for a high operating temperature heat transfer fluids. Due to the decomposition of molten nitrates at temperatures above about 550 °C, molten fluorides or chlorides are expected to be needed for higher temperature operation. KCl-MgCl2 is a promising heat transfer fluid due to its low cost and good thermal transport properties. Corrosion in molten chloride salts can be severe if salt chemistry is not well controlled. Research has shown that the main corrosion mechanism in Fe-Ni-Cr alloys exposed to molten salts is selective oxidation of Cr and that the corrosion mechanism is mass transfer limited. In the research to be presented, thermosiphons were operated at three different temperature ranges to add flow to corrosion tests and evaluate changed corrosion rates. Four alloys were tested in the thermosiphons with varying temperature and with and without Mg redox control. The most extreme case tested had the hot region at ~930 °C and cold region at ~880C. The research found that naturally convective flow could increase up to 5 times the corrosion compared to static tests for Haynes-230 without corrosion inhibition. Corrosion inhibition using Mg worked well to decrease corrosion and mass transfer reactions for Fe, Co, and Ni based superalloys.

Owning to its high photoelectric conversion efficiency and cost-performance ratio, carbon dioxide laser shows great potential as a cutting technique in inorganic-organic composites processing. The cutting process used on alumina green sheet with tungsten steel blade has been reported and widely used in industrial production. But the debris and scraps produced during the cutting process are difficult to be removed, and may induce serious quality issues. These problems can be solved during laser cutting process. Besides, it also has advantages of both maintain high cutting efficiency and low cost. But the application of laser cutting process on alumina green sheet is still restricted, due to the rough edges and dust raised during the process. A new 55w carbon-dioxide laser cutting system with flying light path is reported to processing green sheets of High-Temperature Co-fired Ceramic (HTCC). A prototype based on carbon-dioxide laser is designed and manufactured. Specially designed is the adjustment range of process parameters in the mechanical structure, electric control system and interactive software. In the mechanical part, vacuum cavity structure is optimized, and customized electromagnetic valve for high power vacuum cleaner for alumina green sheet viscous dust is redesigned. The electric control system is realized with IPC-based Hi-precision movement control board and Advantech USB 4751 control card, in order to accurately control the laser parameters, such as laser switching frequency, average power density and laser cutting speed. As for the interactive software, user interface of the program is designed to cover more control parameters, including full manual function and safety control. The effect of laser switching frequency, average power density, laser cutting speed, degree of vacuum at the back of green sheets and coaxial compressed air pressure is analyzed on the surface cleanliness of green sheets, laser cutting efficiency and the cutting quality. The Taguchi method is studied to optimize the experimental design, improving the cutting edge quality and dust quantity on the green sheet cut section.

Three-dimensional (3D) stem cell differentiation cultures recently emerged as a novel model system for investigating human embryonic development and disease progression in vitro, complementing existing animal and two-dimensional (2D) cell culture models. Organoids, the 3D self-organizing structures derived from pluripotent or somatic stem cells, can recapitulate many aspects of structural organization and functionality of their in vivo organ counterparts, thus holding great promise for biomedical research and translational applications. Importantly, faithful recapitulation of disease and development processes relies on the ability to modify the genomic contents in organoid cells. The revolutionary genome engineering technologies, CRISPR/Cas9 in particular, enable investigators to generate various reporter cell lines for prompt validation of specific cell lineages as well as to introduce disease-associated mutations for disease modeling. In this review, we provide historical overviews, and discuss technical considerations, and potential future applications of genome engineering in 3D organoid models.

Design, modification and test of the conduction cooled high-current current leads for the superconducting magnet

Response rates in household surveys are declining, increasing the risk of nonresponse bias in survey estimates. Survey costs are increasing. As a result, design features such as higher monetary incentives are needed but often cannot be afforded. Two or more survey protocols could be implemented in parallel, where some have lower nonresponse while others have lower cost, as long as the data can be combined in a way that reflects the reduced potential for nonresponse bias under the more intensive protocol. We describe the main barrier to the use of such an approach—that traditional methods ignore the expected lower bias in one condition. The proposed approach includes random assignment of sample members to a data collection protocol and adjustment of survey estimates to the superior protocol, based on key survey variables—if differences in estimates are found. This represents a major departure from the current practice in constructing nonresponse adjustments and leverages the use of the same sampling design, survey instrument, and measurement procedures in each condition. An illustrative example is presented using data from a national survey. Methods to address both bias reduction and variance estimation are described. We end with limitations and suggestions for future research.

PurposeFor this paper, the authors focus on Porter’s competitive advantage. Hybrid strategy refers to how a firm creates value vis-à-vis competitors by simultaneously relying on lower costs and greater differentiation to achieve a competitive advantage. This strategy emphasises both and aims to provide much more monetary value to customers through the combination of reduced cost and a higher rate of differentiation. In addition, this research focuses on family small and medium-sized enterprises (SMEs), because they have particularities arising from the incorporation of family members both as owners of the SME and in managerial positions. The porpose of this study is to analyse whether the existing differences produced by the role of the family in strategic decision-making and the concentration of family power have a higher impact on performance and innovation than non-family SMEs.Design/methodology/approachStructural equation modelling was used to analyse Spanish firms with fewer than 250 employees. This study randomly selected SMEs operating in Spain from the Spanish Central Business Directory (2021) database. The overall sample design was based on stratified sampling.FindingsSMEs are facing new challenges, and this has led to the emergence of new competitive strategies. Companies have started to combine differentiation strategies with cost strategies to achieve superior performance and better adapt to these changes. This study confirms a positive relationship between the adoption of hybrid strategies and market performance in SMEs. In addition, hybrid strategy reinforces innovation, which has a mediating role between hybrid strategy and market performance. Finally, the findings indicate that family SMEs achieve a greater impact of hybrid strategy on innovation than non-family SMEs. Moreover, innovation plays a mediating role only in the case of family firms, which enhances the relationship between hybrid strategy and market performance.Originality/valueFor SMEs to survive in turbulent environments, this study proposes the adoption of hybrid strategies instead of pure strategies. The novel model links hybrid strategy (as opposed to “stuck in the middle”), innovation and market performance. The research is valuable for owners and managers of family SMEs because this study finds differences in the relationships studied compared to non-family SMEs.

Designing Sphere-like FeSe2-Carbon Composites with Rational Construction of Interfacial Traits towards Considerable Sodium-storage Capabilities

Techno-economic comparison of wet and dry cooling systems for combined cycle power plants in different climatic zones

Evolutionary neural architecture search (ENAS) automates the design of neural network architectures but incurs significant computational costs during the evaluation phase of candidate neural networks in the evolutionary algorithm. To address this issue, surrogate models are widely adopted to estimate the performance of candidate architectures, thereby reducing resource consumption. However, existing surrogate models are primarily based on regression or classification. They are often hindered by interference from low-quality architectures, which limits search efficiency and final performance. To overcome these challenges, we propose surrogate-assisted neural architecture search with performance clustering (PCNAS). PCNAS introduces a contrastive learning-based performance clustering encoder (PCE). The PCE maps candidate architectures into an embedding space to form high-performance clusters while maximizing separation from low-performance architectures. This design mitigates the negative influence of poor-quality candidates. To enhance the discriminative power of the PCE, we incorporate a staged sample generation strategy to strengthen the hierarchical representation capacity of the PCE. Additionally, we introduce a training-free simple classifier to efficiently select high-performance architectures from the embedding space. PCNAS achieves high accuracy with low computational cost on NAS-Bench-101 and NAS-Bench- 201, outperforming previous approaches. Furthermore, PCNAS exhibits strong efficiency in the DARTS search space, discovering a high-performing architecture with a 2.53% error rate using only 0.5 GPU days of search cost, and on MobileNetV3 with ImageNet, achieving 78.12% top-1 accuracy using only 0.3 GPU days.

Catalysis: The Technology Enabler for New, Low Carbon Energy Technologies